Economics Of Non-Communicable Diseases In Indonesia
Economics ofNon-CommunicableDiseases in IndonesiaApril 2015
ContentsOverview and purpose3NCDs and prevalence of risk factors in Indonesia4Economic burden of NCDs in Indonesia, 2012-20306Comparison between Indonesia, India and China9Conclusion11Appendix: Corrections of the WHO EPIC model in 201512The Economics of Non-Communicable Diseases in Indonesiareport was written by Bloom, D. E., Chen S., McGovern M.,Prettner K., Candeias V., Bernaert A. and Cristin S.World Economic Forum 2015 – All rights reserved.No part of this publication may be reproduced orTransmitted in any form or by any means, includingPhotocopying and recording, or by any informationStorage and retrieval system.REF 090415
Overview and purposeNon-communicable diseases (NCDs) have beenestablished as a clear threat not only to human health, butalso to development and economic growth. Developedby the World Economic Forum, The Economics of NonCommunicable Diseases in Indonesia provides new dataon the economic burden of NCDs in Indonesia and puts itin perspective by comparing this burden to that of India andChina.With this new addition to the series on the Economics ofNCDs, the World Economic Forum aims to advance theunderstanding of the expected economic output loss atthe country level, particularly in countries in economic andepidemiological transition. This document also seeks tostimulate discussion on the extensive impact of NCDs onIndonesian families, businesses and society.The evidence presented here provides a starting point toreorient the dialogue on investing in healthy living and NCDprevention in Indonesia towards the view that a healthypopulation is an important factor for sustainable growth.Focusing on Indonesia, this document includes:1. A snapshot of the prevalence of NCDs and risk factors inIndonesia2. Estimates of lost economic output due to NCDs,focusing on the negative effects of NCDs on the laboursupply3. Comparison of the economic burden of NCDs inIndonesia, India and ChinaThe Economics of Non-Communicable Diseases in Indonesia3
NCDs and prevalence ofrisk factors in IndonesiaNCD burdenOver the past decades, Indonesia has made phenomenalprogress. Per capita income has been increasing at ablistering pace, up to around 3,000 per capita in 2010.At the same time, fertility has dropped dramatically, whilelife expectancy has increased steadily. From an individualperspective, these developments are clearly welcome.However, they also imply an increasing threat of NCDs toIndonesia’s population health and well-being. This threat isbeing realized through two pathways. First, the continuousdrop in fertility and mortality has led to an ageing ofthe society. Second, the economic growth has beenaccompanied by rapid urbanization and the transition tooccupations requiring less physical activity. This has led toa steady increase in the prevalence of modifiable NCD riskfactors such as tobacco use, harmful alcohol use, poor dietand sedentary lifestyles (see Table 1).All of these factors act to raise the risk of susceptibilityto NCDs such as cardiovascular disease and chronicobstructive pulmonary disease.Table 1: Adult NCD risk factors of IndonesiaMales35%Total alcohol per capitaconsumption, in litres of purealcohol (2010)1.10.10.6Raised blood pressure (2008)29.1%26.6%27.8%2.6%6.9%4.8%Obesity (2008)Source: World Health Organization, 2014Indonesia is undergoing an epidemiological transition, withthe disease burden shifting from communicable diseaseand early life mortality to NCDs, increases in life expectancyand increases in median age at death. According toestimates from the World Health Organization (WHO), theproportional mortality due to NCDs has increased from50.7% in 2004 to 71% in 2014 (see Figure 1).Injuries7%Communicable,maternal, perinataland ther NCDs10%4The Economics of Non-Communicable Diseases in IndonesiaTotal3%Figure 1: Cause of death in Indonesia, 2012 (% of total)Source: World Health Organization, 2014Females67%Current tobacco smoking (2011)DiabetesChronic respiratory6%diseases5%Cancers13%
PrevalenceThe most prevalent NCDs in Indonesia today arecardiovascular diseases, cancers, chronic respiratorydiseases and diabetes. In 2012, non-communicablediseases accounted for more disability-adjusted lifeyears (DALYs) than communicable ones ‒ approximately476 million and 240 million DALYs, respectively (WHO,2014).Diabetes is of particular concern ‒ by 2030, the numberof people with diabetes will nearly double, from 7.6 millionin 2013 to 11.8 million. With an annual growth in diabetesprevalence of 6%, this far exceeds the country’s overallannual population growth rate (Blueprint for ChangeProgram, 2013).Mental health conditions, including depression,schizophrenia and bipolar disorder, also contribute heavilyto the country’s NCD burden. Neuropsychiatric disordersare estimated to account for 10.7% of the total burden ofdisease in Indonesia (WHO, 2011).However, Indonesia is still in the midst of this transitionwith communicable, maternal, perinatal and nutritionalconditions accounting for 22% of total deaths, compared tojust 5% in China. As the trend of increasing NCD burden isexpected to continue, inaction is not an option.The Economics of Non-Communicable Diseases in Indonesia5
Economic burden of NCDs inIndonesia, 2012-2030While gathering further evidence to add to ourunderstanding of the consequences of NCDs for individualhealth remains a priority, there is less evidence on theimpact of NCDs on wider society, such as their effecton economic growth. There are many channels throughwhich the consequences of NCDs are expected tomanifest, including the diversion of household or individualconsumption expenditure or savings into healthcare, andreductions in labour supply and productivity.In this analysis, we provide a framework for modelling theimpact of NCDs on economic growth through labour supplyand productivity, and for quantifying the losses associatedwith these diseases. This framework constitutes a tool forevaluating the economic costs associated with NCDs and,as a result, provides an evidence base for policy decisionsin relation to interventions targeted at NCDs.EPIC model to assess the economic output loss forIndonesiaThe economic burden of NCDs is analysed using anupdated and corrected version of the World HealthOrganization (WHO) EPIC model, which allows us toquantify the impact of NCDs on aggregate output. EPIC isbased on an augmented Solow economic growth model inwhich the growth path of national income (GDP) is assumedto depend on technological progress, capital accumulationand changes in (effective) labour supply.The Solow model has been a workhorse framework usedto understand aggregate income growth and differencesin macroeconomic performance since the 1950s. EPICcaptures NCDs’ impact on aggregate output through thelabour supply channel. Specifically, NCDs mortality directlyreduce labour supply by reducing the number of workingage individuals.6The Economics of Non-Communicable Diseases in IndonesiaThe reduction in the size of the labour force then translatesinto a loss in aggregate output through the usual Solowproduction function. Notice that NCD mortality for peoplewho are not in the labour force (retirees, children, etc.)will not affect aggregate output (in contrast to per capitaoutput). Hence, the input data needs to differentiatebetween the disease burdens in different groups.Economic output in each year is modelled according tothe production function approach described above, andforecasts for population structure and NCD prevalence.Then, aggregate income is simulated over the period ofinterest in two scenarios:Status quo scenario: Economic output is modelled for eachyear, taking the NCD prevalence forecasts as given. This isthe case without implementation of interventions that wouldreduce the mortality rate of a disease further than projected.Counterfactual scenario: The case assumes completeelimination of the specified disease with zero cost of theintervention.The economic burden of a specified disease is thencalculated as the undiscounted cumulative differencein projected annual GDP between the two scenariosdescribed above.EPIC has been used to directly model the impact of fiveNCDs: ischemic heart disease, cerebrovascular disease,diabetes, chronic obstructive pulmonary disease (COPD)and breast cancer. To obtain estimates for all NCDs, wescaled up the results presented in the model to reflectthe four leading physical NCD domains (all cardiovasculardiseases, diabetes, chronic respiratory disease andcancers).
The scaling is implemented by calculating the proportionof total morbidity in a particular domain (e.g. cancer) that isaccounted for by the relevant disease in EPIC (e.g. breastcancer). The morbidity contribution of the EPIC disease tothe NCD domain is calculated using the ratio of DALYs forthat disease relative to the NCD domain. DALY estimatesare taken from the latest WHO Global Burden of Disease(GBD) study (2013).Furthermore, the burden of mental health is constructedusing the ratio of the DALYs associated with the fourphysical NCD domains to the DALYs associated with mentalhealth. We plan to expand the framework to provide directestimates of the economic burden associated with allrelevant NCDs in a later updated version of the EPIC model.Data sourcesThe disease-specific mortality projections and thepopulation projection for Indonesia are based on WHOGlobal Burden of Disease estimates through 2030. Labourprojections are based on International Labour Organizationestimates of labour force participation rates. Data oneconomic variables were obtained from Abegunde andStanciole (2006), the World Development Indicators &Global Development Finance database, the InternationalMonetary Fund’s World Economic Outlook database, andthe Penn World Tables.Expected economic output loss for Indonesia: 4.47 trillion lost due to NCDs ( 17,863 per capita)1 from2012 through 2030Table 2 presents the model estimates for the NCD burdenin Indonesia in 2010 US . The first two columns show theWHO disease domains and the diseases addressed inthe EPIC model, respectively. The third column shows theoutput of EPIC for individual diseases. The fourth columnshows the scaling factors calculated from the associatedDALYs. The last column presents the scaled value of thedisease burden in each of the five WHO-defined domains.1Per capita losses are calculated based on the population in 2012Table 2: Scaling of EPIC output for 2012-2030 to match the five WHO NCD domains for IndonesiaWHO diseaseEPIC diseaseEPIC rawoutputDiabetes0.2Ischemic heartdisease0.9CerebrovasculardiseaseRespiratory diseaseCancerDiabetesCardiovasculardiseaseDisease scaling factorScaled raw output in2010 US trillionsDiabetes/1.000.200.46(IHD CBD)/0.771.77COPD0.45COPD/0.5470.82Breast cancer0.07Breast cancer/0.10.70Total physicalMental illnessOverall totalTotal output loss3.49(Total physical)x(0.28)0.984.47Source: AuthorsThe Economics of Non-Communicable Diseases in Indonesia7
The burden varies substantially between diseases. Aswe can see from Figure 2, cardiovascular disease aloneaccounts for 39.6% of the total loss of GDP output and isfollowed by mental health conditions (21.9%) and respiratorydiseases (18.4%). Cancer contributes another 15.7% to thetotal loss, and diabetes accounts for the remaining 4.5%.The costs associated with NCDs in Indonesia aresubstantial. According to our calculations, the fivedomains of NCDs (cardiovascular disease, cancer, chronicobstructive pulmonary disease, diabetes and mental healthconditions) will cost Indonesia 4.47 trillion (or 17,863 percapita)2 from 2012 through 2030.2Per capita losses are calculated based on the population in 2012Figure 2: Contribution of each disease to overall loss of GDP output, Indonesia 30.00%30%35.00%35%40.00%40%45.00%45%Source: AuthorsA total cost estimate of 4.47 trillion due to NCDs from 2012 through 2030 is a substantial amount by any measure: it is 5.1times Indonesia’s GDP in 2012, and almost 170 times Indonesia’s total health expenditure in 20123 (see Figure 3).3Data for total health expenditure is obtained from the Global Health Expenditure Database (GHED) of WHO, updated in 2014Figure 3: Total health expenditure (current US ), Indonesia 1995-201230Health expenditure in current USD 022003Health expenditure, publicSource: Global Health Expenditure Database, World Health Organization, 20148The Economics of Non-Communicable Diseases in Indonesia200420052006Health expenditure, private200720082009201020112012
Comparison betweenIndonesia, India and ChinaThe NCD burden in Indonesia is more severe than amongits neighbours. Figures 5-7 provide comparisons of theoutput lost due to NCDs between Indonesia, India andChina.4 Indonesia will suffer a larger total output loss thanIndia ( 4.47 trillion versus 4.32 trillion) during the period2012-2030, with only one-fifth of India’s population and onehalf of its annual GDP.two countries into account, Indonesia’s NCD burden ismuch larger compared to baseline GDP.During the period 2012-2030, the total NCD-related lossaccruing in China is 3.57 times GDP in 2012, while thecorresponding loss for Indonesia over the same time periodis 5.10 times its GDP. Therefore, NCDs pose a large burdenfor Indonesia’s economy in both absolute and relative terms.China has larger output losses than Indonesia at both theaggregate level ( 29.4 trillion versus 4.47 trillion) and at theper capita level ( 21,794 versus 17,863). However, takingthe differences in economic development between these4 The calculations for China and India follow from Bloom et al. (2014); notice that thevalues are different, since here we updated the results with a corrected version ofWHO EPIC model (See Appendix for details of the corrections)Figure 4: Proportional mortality due to NCDs in Indonesia, India and China, 2014 (% of total deaths, all ages, both uNCDriesatalarNCDOtTotal ard28%Communicable,maternal andperinatalsOther eathIndonesiaCommunSource: World Health Organization, 2014Figure 5: Comparison of lost output between Indonesia, India and China, 2012-2030 (2010 US 0.200.140.590Source: e Economics of Non-Communicable Diseases in Indonesia9
Figure 6: Comparison of lost output per capita between Indonesia, India and China, 2012-2030 (2010 US cer5.694.474.320.980.94MentalHealthChinaSource: AuthorsFigure 7: Comparison of lost output as a percentage of 2012 nominal %IndonesiaSource: Authors10The Economics of Non-Communicable Diseases in 0%600.00%600%Total
ConclusionNCDs are extremely costly for Indonesia. Our analysisestimates that the loss of labour due to NCDs will leadto a substantial reduction in the country’s productivecapacity that is much bigger than those of its neighboursin Asia. Relative to scenarios where interventions aretaken to reduce NCD prevalence, Indonesia’s economicdevelopment is likely to be significantly impeded by NCDs ifthe status quo scenario is maintained.Moreover, the results presented here are likely to beunderestimates of the total impact of NCDs on theIndonesian economy, as the EPIC model currently onlymodels the effect on labour supply. But, as we discussabove, there are many other pathways through which wewould expect NCDs to affect aggregate economic growth.Future updates to the EPIC model will include theseadditional channels.NCDs are imposing a significant burden on Indonesia’seconomy that will only increase in the next two decades.There is a vast body of evidence on effective and costeffective actions that governments, the private sector andcivil society can implement to address the NCD burden(World Economic Forum/WHO, 2011).There are promising estimates of returns on investment(ROI) for interventions to reduce NCDs. Investingin population health not only improves health, but alsocontributes to prosperity and provides both social andfinancial protection. The 2013 Lancet Commission oninvesting in health estimated that, between 2000 and 2011,about 24% of the growth in full income in low-incomeand middle-income countries resulted from the value ofadditional healthy life years gained. In South Asia, theannual value of the reduction in mortality was equivalent to2.9% of the average income during the period 2000 to 2011,which is almost half the size of the value of the increase inGDP (Jamison, 2013).The joint World Economic Forum/Harvard Schoolof Public Health report on the Economics of NonCommunicable Diseases in India (2014) calculated theROI of 12 interventions ongoing in India. The interventionsthat focused on screening (for hypertension), vaccination(HPV) and reduced tobacco consumption were particularlypromising in terms of the feasibility of achieving a 15% ROI.Other interventions that focused on reducing salt intake orimproving care for depressive and anxiety disorders alsopresented promising ROI values.Other assessments of the potential ROI of investingin population health published in 2015 also pointed topromising results ranging between 90% and 3,700% ROI(World Economic Forum, 2015).One interesting example comes from the work of the HealthPromotion Board of Singapore to reduce the intake ofsaturated fat through subsidies for meals eaten outside thehome which had a higher composition of healthier oils. It isestimated that this intervention will have a ROI of more than1,100% by 2020. The programme is estimated to replace1,860 DALYs with healthy life years. This could result in atremendous economic return for Singapore, estimated atS 102 million by 2020. The ROI of more than 1,100% isespecially impressive given the fact that some benefits,such as reduced healthcare costs, were not included in theanalysis, resulting in a more conservative estimate.5Kaiser Permanente, an integrated healthcare provider inthe United States covering more than 9 million people, setup a programme to treat 350,000 high-risk patients with amedication bundle, including aspirin, a statin and an ACEinhibitor. In addition, partnerships with community-basedhealth systems helped to further extend the programme totheir patient populations. The programme has a direct costof 205,000 per 1,000 participating patients and prevents19 heart attacks or strokes per 1,000 participating patientsper year, which results in 147 fewer unhealthy years per1,000 high-risk patients. Those additional healthy life yearshave a socio-economic value of 7.8 million, giving a ROI of3,700%.6Efficient allocation of resources. Given the largedisparities in the disease-specific burden as well as in thetreatment costs associated with specific diseases, limitedresources should be carefully allocated to both treatmentand prevention initiatives, according to guidance from costeffectiveness analysis and the national context.All stakeholders can benefit from investing in maximizinghealthy life years and help move the current landscapefrom “healthy as a cost” to “healthy as an investment”,particularly when it comes to investing in the prevention ofthe largest killers of the decade: NCDs. Taking a holisticand systemic approach ‒ in which all public and privatestakeholders understand the full range of costs and benefitsthat can be incurred to their business, public policiesand societies ‒ will lead to a step-change in the healthinvestment agenda.World Economic Forum, Maximizing Healthy Life Years: Investments that Pay Off,January 20156Ibid5The Economics of Non-Communicable Diseases in Indonesia11
AppendixCorrections of the World Health Organization’s EPICmodel in 2015Major problems:–– Inconsistency of the definition of labour. The originalEPIC model fails to use a consistent definition of labourthroughout the calculations (working population versuseffective labour). Notice that effective labour is calculatedas the product of working population and experiencefactors. The labour projection is the number in theworking population rather than effective labour. Andthis number is used as the labour input for status quoeconomic projections. However, when calculating theeffect of mortality, additional effective labour from themortality decline is added to the pure number of theworking population, which is not correct. Instead, in ourupdated version of the model, we modified the code byusing “effective labour” rather than working population inall calculations.–– Wrong update function for physical capital. The functionfor calculating aggregate capital is not correct, it shouldbe:Instead of:Here sYt-1 represents the savings at time period t-1 thatare invested to generate physical capital in the next timeperiod t. This (coding) error results in savings always beingset to zero, which implies that aggregate capital continuallydepreciates over time and is never augmented.Minor problems:–– In the calculations, the treatment cost is always set as 0.50 for all diseases and all countries.–– Morbidity is not factored into the model, despite beingnominally present in the original EPIC programme.–– It is not possible to change the starting year for theanalysis. Although the model allows for input of startingyear, the starting year GDP value is always set to thevalue of 2005, which renders the calculation incorrect.Because 2005 is always taken as the base year, it isnot possible to calculate losses for other periods, forexample, 2012-2030, only periods starting from 2005.12The Economics of Non-Communicable Diseases in Indonesia
ReferencesAbegunde, Dele, and Anderson Stanciole. “An estimationof the economic impact of chronic noncommunicablediseases in selected countries”. World Health Organization,Department of Chronic Diseases and Health Promotion,2006.Bloom, D.E. et al. “The Macroeconomic Impact of Noncommunicable Diseases in China and India: Estimates,Projections, and Comparisons”. The Journal of theEconomics of Ageing, 2014.Bloom, D.E., Cafiero-Fonseca E.T., Candeias V, Adashi E.,Bloom L., Gurfein L., Jané-Llopis E., Lubet, A., MitgangE, Carroll O’Brien J, Saxena A. Economics of NonCommunicable Diseases in India: The Costs and Returnson Investment of Interventions to Promote Healthy Livingand Prevent, Treat, and Manage NCDs. World EconomicForum, Harvard School of Public Health, 2014.UNICEF Indonesia, ources/VR-14-038.pdf, July 2014.“Where economics and health meet: changingdiabetes in Indonesia”. The Blueprint for ChangeProgramme, Novo Nordisk. DFs/Blueprint-for-changeIndonesia--52383 Korr19.pdf, March 2013.World Economic Forum, World Health Organization. FromBurden to “Best Buys”: Reducing the Economic Impact ofNon-Communicable Diseases in Low- and Middle-IncomeCountries. Geneva, 2011.World Economic Forum. Maximizing Healthy Life Years:Investments that Pay thy-lifeyears-investments-pay, January 2015.Country Profiles Indonesia, WHO Report on the GlobalTobacco Epidemic, ntry profile/idn.pdf?ua 1, 2013.Estimated DALYs (’000) by cause, sex and WHO MemberState, 2012, Department of Health Statistics and InformationSystems, World Health Organization, May 2014.GBD Profile: Indonesia, Institute for health Metrics andEvaluation. s/country profiles/GBD/ihme gbd country reportindonesia.pdf, November 2010.Jamison, D.T. et al. (2013). Global health 2035: a worldconverging within a generation. The Lancet, 382 (9908),1898-55.“The Economist: For Big Tobacco, South-East Asia is thefinal frontier”, NCD Alliance. http://www.ncdalliance.org/node/3330, April 2011.Mental Health Atlas 2011 – Indonesia, WHO. http://www.who.int/mental health/evidence/atlas/profiles/idn mhprofile.pdf, 2011.NonCommunicable Diseases (NCD) Country Profiles, WHO.http://www.who.int/nmh/countries/idn en.pdf, 2014.The Economics of Non-Communicable Diseases in Indonesia13
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